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Diffstat (limited to 'runtimes/libs/ARMComputeEx/arm_compute/runtime/CL/functions/CLTransposeConvLayer.h')
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diff --git a/runtimes/libs/ARMComputeEx/arm_compute/runtime/CL/functions/CLTransposeConvLayer.h b/runtimes/libs/ARMComputeEx/arm_compute/runtime/CL/functions/CLTransposeConvLayer.h new file mode 100644 index 000000000..340a7bfe9 --- /dev/null +++ b/runtimes/libs/ARMComputeEx/arm_compute/runtime/CL/functions/CLTransposeConvLayer.h @@ -0,0 +1,157 @@ +/* + * Copyright (c) 2019 Samsung Electronics Co., Ltd. All Rights Reserved + * Copyright (c) 2017-2018 ARM Limited. + * + * SPDX-License-Identifier: MIT + * + * Permission is hereby granted, free of charge, to any person obtaining a copy + * of this software and associated documentation files (the "Software"), to + * deal in the Software without restriction, including without limitation the + * rights to use, copy, modify, merge, publish, distribute, sublicense, and/or + * sell copies of the Software, and to permit persons to whom the Software is + * furnished to do so, subject to the following conditions: + * + * The above copyright notice and this permission notice shall be included in all + * copies or substantial portions of the Software. + * + * THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR + * IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, + * FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE + * AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER + * LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, + * OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE + * SOFTWARE. + */ +#ifndef __ARM_COMPUTE_CLTRANSPOSECONVLAYER_H__ +#define __ARM_COMPUTE_CLTRANSPOSECONVLAYER_H__ + +#include "arm_compute/runtime/CL/functions/CLConvolutionLayer.h" +#include "arm_compute/runtime/CL/functions/CLTransposeConvLayerUpsample.h" + +#include "arm_compute/core/CPP/kernels/CPPFlipWeightsKernel.h" + +#include "arm_compute/runtime/CL/CLMemoryGroup.h" +#include "arm_compute/runtime/CL/CLTensor.h" +#include "arm_compute/runtime/IFunction.h" +#include "arm_compute/runtime/IMemoryManager.h" + +#include <memory> + +namespace arm_compute +{ +class ICLTensor; +/** Function to run the transpose convolution layer. + * + * @note This layer was copied in order to fix a bug computing to wrong output dimensions. + * + * TransposeConv Layer is the backward pass of Convolution Layer. First we transform the input + * depending on the stride and pad info and then perform a 1x1 + * convolution pass. Input stride defines how many zeroes we should put between each element of the + * input, pad is the amount of padding and finally a is a user + * specified value where a < stride - 1, that increases the padding top and right of the input + * image. + * + * The relation between input to output is as follows: + * \f[ + * width\_output = (width\_input - 1) \cdot stride\_x - \cdot padding\_x + kernel\_x + * \f] + * \f[ + * height\_output = (height\_input - 1) \cdot stride\_y - \cdot padding\_y + kernel\_y + * \f] + * + * where: + * width_input is the size of the first input dimension. + * height_input is the size of the second input dimension. + * width_output is the size of the first output dimension. + * height_output is the size of the second output dimension. + * kernel_x and kernel_y are the convolution sizes in x and y. + * stride_x and stride_y is the input stride of the first and second dimension. + * + * The weights used by Deconvolution are supposed to be the same as the ones used for Convolution. + * Therefore, it will be necessary to use the weights in the + * reverse order to perform an actual convolution. This is achieved by using the @ref + * CPPFlipWeightsKernel. + * + * This function calls the following OpenCL kernels/functions: + * + * -# @ref CLTransposeConvLayerUpsample + * -# @ref CLConvolutionLayer + * + */ +class CLTransposeConvLayer : public IFunction +{ +public: + /** Constructor */ + CLTransposeConvLayer(std::shared_ptr<IMemoryManager> memory_manager = nullptr); + /** Prevent instances of this class from being copied (As this class contains pointers) */ + CLTransposeConvLayer(const CLTransposeConvLayer &) = delete; + /** Default move constructor */ + CLTransposeConvLayer(CLTransposeConvLayer &&) = default; + /** Prevent instances of this class from being copied (As this class contains pointers) */ + CLTransposeConvLayer &operator=(const CLTransposeConvLayer &) = delete; + /** Default move assignment operator */ + CLTransposeConvLayer &operator=(CLTransposeConvLayer &&) = default; + /** Set the input, weights, biases and output tensors. + * + * @param[in,out] input Input tensor. 3 lower dimensions represent a single input, + * and an optional 4th dimension for batch of inputs. + * Data types supported: QASYMM8/F16/F32. + * @param[in] weights The 4d weights with dimensions [width, height, IFM, OFM]. + * Data type supported: Same as @p input. + * @param[in] bias (Optional) The biases have one dimension. Data type supported: + * Same as @p input. + * @param[out] output Output tensor. The output has the same number of dimensions + * as the @p input. + * @param[in] info Contains padding and policies to be used in the + * transpose convolution, this is decribed in @ref PadStrideInfo. + * @param[in] invalid_right The number of zeros added to right edge of the output. + * @param[in] invalid_bottom The number of zeros added to top edge of the output. + * @param[in] weights_info (Optional) Weights information needed for @ref + * CLConvolutionLayer, specifies if the weights tensor has been + * reshaped with @ref CLWeightsReshapeKernel. + */ + void configure(ICLTensor *input, ICLTensor *weights, const ICLTensor *bias, ICLTensor *output, + const PadStrideInfo &info, unsigned int invalid_right, unsigned int invalid_bottom, + const WeightsInfo &weights_info = WeightsInfo()); + /** Static function to check if given info will lead to a valid configuration of @ref + * CLTransposeConvLayer + * + * @param[in] input Input tensor info. 3 lower dimensions represent a single input, + * and an optional 4th dimension for batch of inputs. + * Data types supported: QASYMM8/F16/F32. + * @param[in] weights The 4d weights info with dimensions [width, height, IFM, OFM]. + * Data type supported: Same as @p input. + * @param[in] bias (Optional) The biases have one dimension. Data type supported: + * Same as @p input. + * @param[in] output Output tensor info. The output has the same number of dimensions + * as the @p input. + * @param[in] info Contains padding and policies to be used in the + * transpose convolution, this is decribed in @ref PadStrideInfo. + * @param[in] innvalid_right The number of zeros added to right edge of the output. + * @param[in] invalid_bottom The number of zeros added to top edge of the output. + * @param[in] weights_info (Optional) Weights information needed for @ref CLConvolutionLayer, + * specifies if the weights tensor has been reshaped with @ref + * CLWeightsReshapeKernel. + * @return a status + */ + static Status validate(const ITensorInfo *input, const ITensorInfo *weights, + const ITensorInfo *bias, ITensorInfo *output, const PadStrideInfo &info, + unsigned int innvalid_right, unsigned int invalid_bottom, + const WeightsInfo &weights_info = WeightsInfo()); + + // Inherited methods overridden: + void run() override; + void prepare() override; + +private: + CLMemoryGroup _memory_group; + CLTransposeConvLayerUpsample _scale_f; + CLConvolutionLayer _conv_f; + CPPFlipWeightsKernel _flip_weights; + CLTensor _scaled_output; + ICLTensor *_original_weights; + CLTensor _weights_flipped; + bool _is_prepared; +}; +} +#endif /* __ARM_COMPUTE_CLTRANSPOSECONVLAYER_H__ */ |